Search

Formate oxidase (FOx), which contains 8-formyl flavin adenine dinucleotide (FAD), exhibits a distinct advantage in utilizing ambient oxygen molecules for the oxidation of formic acid compared to other glucose-methanol-choline (GMC) oxidoreductase enzymes that contain only the standard FAD cofactor. The FOx-mediated conversion of FAD to 8-formyl FAD results in an approximate 10-fold increase in formate oxidase activity. However, the mechanistic details underlying the autocatalytic formation of 8-formyl FAD are still not well understood, which impedes further utilization of FOx. In this study, we employ molecular dynamics simulation, QM/MM umbrella sampling simulation, enzyme activity assay, site-directed mutagenesis, and spectroscopic analysis to elucidate the oxidation mechanism of FAD to 8-formyl FAD. Our results reveal that a catalytic water molecule, rather than any catalytic amino acids, serves as a general base to deprotonate the C8 methyl group on FAD, thus facilitating the formation of a quinone-methide tautomer intermediate. An oxygen molecule subsequently oxidizes this intermediate, resulting in a C8 methyl hydroperoxide anion that is protonated and dissociated to form OHC-RP and OH−. During the oxidation of FAD to 8-formyl FAD, the energy barrier for the rate-limiting step is calculated to be 22.8 kcal/mol, which corresponds to the required 14-hour transformation time observed experimentally. Further, the elucidated oxidation mechanism reveals that the autocatalytic formation of 8-formyl FAD depends on the proximal arginine and serine residues, R87 and S94, respectively. Enzymatic activity assay validates that the mutation of R87 to lysine reduces the kcat value to 75% of the wild-type, while the mutation to histidine results in a complete loss of activity. Similarly, the mutant S94I also leads to the deactivation of enzyme. This dependency arises because the nucleophilic OH− group and the quinone-methide tautomer intermediate are stabilized through the noncovalent interaction provided by R87 and S94. These findings not only explain the mechanistic details of each reaction step but also clarify the functional role of R87 and S94 during the oxidative maturation of 8-formyl FAD, thereby providing crucial theoretical support for the development of novel flavoenzymes with enhanced redox properties. [ABSTRACT FROM AUTHOR]

Ground motion target recognition based on seismic signals is more convenient and efficient than traditional manual patrol identification. However, current high-precision identification methods are limited to single-target classification. In this paper, the embedded adaptive learning technology was utilized to solve the problem of timeliness for the real-time moving target monitoring. We propose a deep bidirectional long short-term memory (DBiLSTM) algorithm that is implemented based on extracting spatial properties. The sequence data is processed by using three models including the convolutional neural network (CNN) and CNN-LSTM and CNN-DBiLSTM respectively, the target labels are categorized in the last layer. Identification results on the JL dataset are indicated that the CNN-DBiLSTM model produces the best performance. The algorithm we proposed improves the identification accuracy by 3.26% compared with the benchmark CNN method and the total number of layers of the network is only five. And the stability is the best among the three algorithms in ten independent experiments. Which Provides a practical classification and identification method for real-time target monitoring system. [ABSTRACT FROM AUTHOR]

Self-attention, which allows transformers to capture deep bidirectional contexts, plays a vital role in BERT-like pre-trained language models. However, the maximum likelihood pre-training objective of BERT may produce an anisotropic word embedding space, which leads to biased attention scores for high-frequency tokens, as they are very close to each other in representation space and thus have higher similarities. This bias may ultimately affect the encoding of global contextual information. To address this issue, we propose TOCOL, a TOken-Level COntrastive Learning framework for improving the contextual representation of pre-trained language models, which integrates a novel self-supervised objective to the attention mechanism to reshape the word representation space and encourages PLM to capture the global semantics of sentences. Results on the GLUE Benchmark show that TOCOL brings considerable improvement over the original BERT. Furthermore, we conduct a detailed analysis and demonstrate the robustness of our approach for low-resource scenarios. [ABSTRACT FROM AUTHOR]

Background: Left ventricular enlargement (LVE) is a common manifestation of cardiac remodeling that is closely associated with cardiac dysfunction, heart failure (HF), and arrhythmias. This study aimed to propose a machine learning (ML)-based strategy to identify LVE in HF patients by means of pulse wave signals. Method: We constructed two high-quality pulse wave datasets comprising a non-LVE group and an LVE group based on the 264 HF patients. Fourier series calculations were employed to determine if significant frequency differences existed between the two datasets, thereby ensuring their validity. Then, the ML-based identification was undertaken by means of classification and regression models: a weighted random forest model was employed for binary classification of the datasets, and a densely connected convolutional network was utilized to directly estimate the left ventricular diastolic diameter index (LVDdI) through regression. Finally, the accuracy of the two models was validated by comparing their results with clinical measurements, using accuracy and the area under the receiver operating characteristic curve (AUC-ROC) to assess their capability for identifying LVE patients. Results: The classification model exhibited superior performance with an accuracy of 0.91 and an AUC-ROC of 0.93. The regression model achieved an accuracy of 0.88 and an AUC-ROC of 0.89, indicating that both models can quickly and accurately identify LVE in HF patients. Conclusion: The proposed ML methods are verified to achieve effective classification and regression with good performance for identifying LVE in HF patients based on pulse wave signals. This study thus demonstrates the feasibility and potential of the ML-based strategy for clinical practice while offering an effective and robust tool for diagnosing and intervening ventricular remodeling. [ABSTRACT FROM AUTHOR]

Adenomyosis (ADS) is a common benign gynecological disease. Abnormal proliferation at the endometrial-myometrial interface (EMI) plays a crucial role in the occurrence and progression of ADS. miR-141-3p is associated with cell proliferation and apoptosis. However, the specific mechanism of miR-141-3p in the etiology of ADS is still unknown. In this study, we explored the effects of miR-141-3p on the proliferation and apoptosis of ADS EMI smooth muscle cells (SMCs). We collected EMI tissues for the primary culture of SMCs from 25 patients diagnosed with ADS and 20 without ADS. Real-time quantitative polymerase chain reaction and western blot were used to measure the mRNA and protein expression levels of miR-141-3p, JAK2, STAT3, phospho-JAK2, and phospho-STAT3 in ADS EMI SMCs. The cell counting kit 8 assay and flow cytometry analysis were used to evaluate the proliferation and apoptosis of EMI SMCs. The miR-141-3p mimic/inhibitor was used to increase or decrease the expression level of miR-141-3p. We added WP1066 to block the phosphorylation of JAK2/STAT3 pathway components. The miR-141-3p levels were decreased, while JAK2 and STAT3 levels were increased in ADS EMI SMCs. miR-141-3p overexpression significantly inhibited the proliferation and enhanced the apoptosis of EMI SMCs, whereas a decrease in miR-141-3p expression level was connected to the opposite results. Meanwhile, inactivated JAK2/STAT3 pathway decreased proliferation and enhanced apoptosis of EMI SMCs after WP1066 treatment. Furthermore, rescue experiments confirmed that the JAK2/STAT3 pathway was the downstream pathway of miR-141-3p and reduced the effect of miR-141-3p on the proliferation and apoptosis of EMI SMCs. These results demonstrate that miR-141-3p regulates the proliferation and apoptosis of ADS EMI SMCs by modulating the JAK2/STAT3 pathway. [ABSTRACT FROM AUTHOR]

In urban stochastic transportation networks, there are specific links that hold great importance. Disruptions or failures in these critical links can lead to reduced connectivity within the road network. Under this circumstance, this manuscript proposed a novel identification of critical links mathematical optimization model based on the optimal reliable path with consideration of link correlations under demand uncertainty. The method presented in this paper offers a solution to bypass the necessity of conducting a full scan of the entire road network. Due to the non-additive and non-linear properties of the proposed model, a modified heuristic algorithm based on K-shortest algorithm and inequality technical is presented. The numerical experiments are conducted to show that improve a certain road link may not necessarily improve the overall traffic conditions. Moreover, the results indicate that if the travel time reliability is not considered, it will bring errors to the identification of key links. [ABSTRACT FROM AUTHOR]

Background: Centromeres play a crucial and conserved role in cell division, although their composition and evolutionary history in green algae, the evolutionary ancestors of land plants, remains largely unknown. Results: We constructed near telomere-to-telomere (T2T) assemblies for two Trebouxiophyceae species, Chlorella sorokiniana NS4-2 and Chlorella pyrenoidosa DBH, with chromosome numbers of 12 and 13, and genome sizes of 58.11 Mb and 53.41 Mb, respectively. We identified and validated their centromere sequences using CENH3 ChIP-seq and found that, similar to humans and higher plants, the centromeric CENH3 signals of green algae display a pattern of hypomethylation. Interestingly, the centromeres of both species largely comprised transposable elements, although they differed significantly in their composition. Species within the Chlorella genus display a more diverse centromere composition, with major constituents including members of the LTR/Copia, LINE/L1, and LINE/RTEX families. This is in contrast to green algae including Chlamydomonas reinhardtii, Coccomyxa subellipsoidea, and Chromochloris zofingiensis, in which centromere composition instead has a pronounced single-element composition. Moreover, we observed significant differences in the composition and structure of centromeres among chromosomes with strong collinearity within the Chlorella genus, suggesting that centromeric sequence evolves more rapidly than sequence in non-centromeric regions. Conclusions: This study not only provides high-quality genome data for comparative genomics of green algae but gives insight into the composition and evolutionary history of centromeres in early plants, laying an important foundation for further research on their evolution. [ABSTRACT FROM AUTHOR]

Pulse wave, as a message carrier in the cardiovascular system (CVS), enables inferring CVS conditions while diagnosing cardiovascular diseases (CVDs). Heart failure (HF) is a major CVD, typically requiring expensive and time-consuming treatments for health monitoring and disease deterioration; it would be an effective and patient-friendly tool to facilitate rapid and precise non-invasive evaluation of the heart's blood-supply capability by means of powerful feature-abstraction capability of machine learning (ML) based on pulse wave, which remains untouched yet. Here we present an ML-based methodology, which is verified to accurately evaluate the blood-supply capability of patients with HF based on clinical data of 237 patients, enabling fast prediction of five representative cardiovascular function parameters comprising left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVDd), left ventricular end-systolic diameter (LVDs), left atrial dimension (LAD), and peripheral oxygen saturation (SpO2). Two ML networks were employed and optimized based on high-quality pulse wave datasets, and they were validated consistently through statistical analysis based on the summary independent-samples t-test (p > 0.05), the Bland–Altman analysis with clinical measurements, and the error-function analysis. It is proven that evaluation of the SpO2, LAD, and LVDd performance can be achieved with the maximum error < 15%. While our findings thus demonstrate the potential of pulse wave-based, non-invasive evaluation of the blood-supply capability of patients with HF, they also set the stage for further refinements in health monitoring and deterioration prevention applications. [ABSTRACT FROM AUTHOR]

This study investigates the joint replenishment and delivery problem taking trade credits the delay in payment permitted by suppliers and capacity-constrained into consideration (CJRD-TC). The CJRD-TC aims to minimize the total system costs by finding a reasonable replenishment and delivery schedule policy. In this paper, an opposite-based RUNge Kutta optimization algorithm (OBRUN) is proposed to compare with other intelligent algorithms, including the differential evolution (DE), RUNge Kutta optimization algorithm (RUN), sine cosine algorithm (SCA), and adaptive differential evolution with optimal external archive (JADE). The proposed algorithm is tested on 14 optimization functions. The values of average, standard deviation, and the best are the lowest for 12 functions, which demonstrates OBRUN is superior to other algorithms. We also provide graphs of search history, 2D views of functions, trajectory curve, average fitness history, and convergence curve of OBRUN, the balance between exploration and exploitation over the course of iterations can be observed. The convergence curves of five algorithms are also depicted, which show OBRUN has a fast convergence rate and accuracy than other algorithms. We conduct numerical experiments, parameter tuning, and sensitivity analysis for each of the small-scale, medium-scale, and large-scale number of items. The OBRUN can always find better solutions with the lowest mean values and the best-found total cost results than other algorithms. Indicators of the average optimality gap and the optimality gap dominate by the value of zero. These computational results have demonstrated OBRUN is a suitable and effective candidate for managers to solve the practical CJRD-TC problems. [ABSTRACT FROM AUTHOR]

Organizations that compete for attention in the marketplace face a strategic decision: whether to target a specialized niche or diversify to reach a broader market. Previous research has extensively analyzed the specialization dilemma faced by for-profit firms. We extend the analysis to knowledge-sharing groups in the marketplace of ideas. Using data on over 1,500 technology groups collected from an online event-organizing platform over a fifteen-year period, we measure the effect of topical focus, rarity, novelty, and technical exclusivity on audience growth, retention, and sustained engagement. We find that knowledge-sharing groups benefit marginally by specializing in rare topics but not in new topics. The strongest predictor of growth and survival is whether the group is associated with technically sophisticated topics, regardless of the breadth of focus, even though technical topics are less widely accessible. We conclude that what matters is not how specialized the organization, but how the organization is specialized. [ABSTRACT FROM AUTHOR]

Being a typical city of heavy industry in west China, Urumqi City is subjected to serious atmospheric ozone pollution in the urban areas due to rapid industrialization and urbanization development. In order to probe into the characteristics of the City' s land-surface ozone pollution, the monitoring data of air pollutants and the meteorological observation data from 2015 to 2019 were applied with the statistical analysis, backward trajectory analysis, potential source contribution factor (PSCF) and concentration weighted trajectory (CWT) to analyze the characteristics and potential source-areas of ozone pollution in Urumqi. The results showed (1) the annual evaluation index of ozone during the period (2015-2019) increased from 118 µg/m³ to 128 µg/m³, and at the same time, the main air pollutant in Urumqi has underwent a transition, i.e, from PM to ozone, the proportion of ozone as a primary pollutant up from 5.8% (2015) to 28.0% (2019). The ozone concentrations variation characteristics of seasons in order of decreasing magnitude: summer>spring>autumn>winter; on the interannual scale, ozone was negatively correlated to NO2 and CO obviously; (2) according to the backward trajectory analysis, the airflow that affected the distribution of atmospheric ozone in Urumqi was characterized by that passing from outbound areas, long-distance migration and containing high ozone concentration. The airflow migration path within the city territory was generally short, not very much influencing the transmission of ozone concentration in Urumqi; and (3) results of using PSCF and the concentration CWT showed that the main source-areas and high ozone-contribution areas that affected the ozone concentration in Urumqi were Changji Prefecture, Tacheng District, Bortala Mongolian Autonomous Prefecture and Altay District; and the distribution of ozone source-areas and high ozone-contribution areas was positively correlated to the seasonal variation of ozone concentrations, which had the evident seasonal characteristics, i.e., the potential source-areas in summer were mainly the moderate source-areas, which widely distributed within the city and had higher ozone contribution, while in winter the whole area of Urumqi turned into a mild source-area; as to spring and autumn the feature of the source-areas fell in between. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China has played an important role in the achievement of the global CO2 emissions mitigation goal. The monitoring and analysis of CO2 emissions in the Yangtze River Economic Belt (YREB) urban agglomerations is strategic to the carbon peak and carbon neutrality in China. In this paper, we revealed the spatial and temporal variations of CO2 emissions in Cheng-Yu urban agglomeration (CY-UA), Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and Yangtze River Delta urban agglomeration (YRD-UA) in YREB and investigated the carbon emission development stage of YREB urban agglomerations. Particularly, a carbon emission development stage framework that considered the relationship between economic growth and carbon emissions was built based on Environmental Kuznets Curves (EKCs). Meanwhile, multiscale geographically weighted regression (MGWR) was used to analyze the impact of different influencing factors, including population (POP), GDP per capita (GDPPC), the proportion of secondary industry (SI), carbon emission intensity (CI), and urbanization (UR), on the CO2 emissions of three urban agglomerations. The results illustrate the following: (1) The CO2 emissions of YREB urban agglomerations decreased, with YRD-UA having the highest CO2 emissions among the three urban agglomerations and contributing 41.87% of YREB CO2 emissions in 2017. (2) CY-UA, YRMR-UA, and YRD-UA reached the CO2 emissions peak in 2012, 2011, and 2020, respectively, all of which are at the low-carbon stage. (3) POP and GDPPC show the greatest impact on the CO2 emissions of the three YREB urban agglomerations. [ABSTRACT FROM AUTHOR]

The typical treatment of waste plastics has become a global environmental problem. In light of recent developments, waste plastics used as asphalt modifiers offer an efficient approach to solve this problem. This paper studied the effects of three kinds of waste plastic-modified asphalts (WPMA), with polypropylene (PP), polyethylene (PE) and ethylene-vinyl acetate copolymer (EVA) as their respective modifiers, on the conventional asphalt performance. Furthermore, an orthogonal experimental design (OED) was used to determine the preparation parameters of WPMA. Thereafter, thermogravimetric-differential scanning calorimetry (TG-DSC) and Fourier transform infrared spectroscopy (FTIR) were employed to expound the mechanism of WPMA. It was then subsequently ascertained that the optimum preparation parameters of PP-modified asphalt (PPMA) and PE-modified asphalt (PEMA) were 170 °C, 3000 rpm, and 30 min, while the optimum preparation parameters of EVA-modified asphalt (EVAMA) were 180 °C, 3000 rpm, and 30 min. In addition, WPMA displayed better high-temperature performance and are inherently more suitable for pavement in high-temperature regions. Ultimately, this study will effectively solve the disposal of waste plastic and promote the research and application of WPMA in the future. [ABSTRACT FROM AUTHOR]

Organic carbon derived from terrestrial plants contributes to aquatic consumers, e.g., zooplankton in lakes. The degree of the contribution depends on the availability of terrestrial organic carbon in lake organic pool and the transfer efficiency of the carbon. Terrestrial organic carbon is poor-quality food for zooplankton with a mismatch of nutrition content and was incorporated to zooplankton with much lower efficiency than phytoplankton. Contributions of terrestrial carbon to zooplankton generally decrease with an increase in phytoplankton production, indicating a preferential incorporation of phytoplankton in previous investigations. However, in eutrophic lakes, the dominating cyanobacteria were of poor quality and incorporated to consumers inefficiently too. In that case, zooplankton in eutrophic wetlands, where cyanobacteria dominate the phytoplankton production and massive terrestrial plants are inundated, may not preferentially incorporate poor food-quality phytoplankton resource to their biomass. Therefore, we hypothesize that carbon contributions of terrestrial vegetation to zooplankton and to lake particulate organic pool should be similar in such aquatic ecosystems. We tested this hypothesis by sampling zooplankton and carbon sources in Ming Lake (Jinan University Campus, southern China) which was overgrown by terrestrial plants after drying and re-flooded. After 60 days of observations at weekly (or biweekly) intervals, applying stable carbon (13C), nitrogen (15 N), and hydrogen (2H) isotopic analysis and a stable isotope mixing model, we estimated the occurrence of extensive carbon contribution (≥ 50%) of flooded terrestrial plants to cladocerans and copepods. Contribution of inundated terrestrial plants to cladocerans was similar to that to lake particulate organic pool. Thus, our study quantified the role of terrestrial carbon in eutrophic wetlands, enhancing our understanding of cross-ecosystem interactions in food webs with an emphasis on the resource quality. [ABSTRACT FROM AUTHOR]

Trade credit is a significant form of short-term financing in the real business situation. This study proposes a practical multi-warehouse joint replenishment and delivery (MJRD) problem under trade credit in accordance with the realistic situation. The goal of the MJRD is to find the reasonable basic replenishment cycle time, the joint replenishment frequency, the delivery frequency, and the assignment information of suppliers to minimize the total cost. Five intelligent algorithms, which include a differential evolution algorithm, genetic algorithm, adaptive hybrid differential evolution algorithm, arithmetic optimization algorithm (AOA), and hybrid arithmetic optimization algorithm (HAOA), are designed to find a solution to this MJRD problem under trade credit. The results of several experiments show that HAOA is effective in solving the proposed MJRD. Compared with AOA, the best improvement is 46.66%. HAOA is a satisfactory algorithm for the proposed MJRD under trade credit. [ABSTRACT FROM AUTHOR]

Terrestrial inputs of dissolved organic matter (DOM) stimulate microbial growth by supplying organic carbon and DOM‐associated nutrients, and thus increase food availability for zooplankton. Terrestrial inputs of DOM might decrease the content of eicosapentaenoic acid (EPA) in particular organic matter (POM) due to an increase in biomass of EPA‐poor microbes, for example, heterotrophic bacteria and autotrophic cyanobacteria, thereby reducing food quality and filter‐feeding zooplankton's biomass. We performed a 26‐d mesocosm experiment where terrestrial DOM was manipulated by adding (treatments) and kept without adding (controls) 13C‐labeled maize leachate to evaluate the effect of food quality changes induced by terrestrial DOM inputs on zooplankton. DOM addition treatments had significantly higher concentrations of POM and Chlorophyll a relative to controls, but significant lower EPA content of POM, responding to increased biomass of bacteria and chlorophytes. Biomass and EPA content of filter‐feeding cladoceran Chydorus sphaericus was significantly reduced by terrestrial DOM addition. Stable isotope analyses showed 13C enrichments in bacteria and cryptophytes in the treatment of 13C‐labeled maize leachate, indicating a growth stimulation of heterotrophic microbes by organic carbon addition. Although the 13C enrichment in Chydorus evidenced the extensive use of terrestrial DOM by this cladoceran, positive relationships between Chydorus biomass and EPA content of POM suggest that terrestrial DOM inputs increase food quality constrains on filter‐feeding zooplankton. Our study suggests that the response of filter‐feeding zooplankton to inputs of terrestrial DOM depends on how the terrestrial inputs change the microbial communities and thus the food quality in the receiving aquatic ecosystems. [ABSTRACT FROM AUTHOR]

This study proposes an effective wind speed forecasting model combining a data processing strategy, neural network predictor, and parameter optimization method. (a) Variational mode decomposition (VMD) is adopted to decompose the wind speed data into multiple subseries where each subseries contains unique local characteristics, and all the subseries are converted into two-dimensional samples. (b) A gated recurrent unit (GRU) is sequentially modeled based on the obtained samples and makes the predictions for future wind speed. (c) The grid search with rolling cross-validation (GSRCV) is designed to simultaneously optimize the key parameters of VMD and GRU. To evaluate the effectiveness of the proposed VMD-GRU-GSRCV model, comparative experiments based on hourly wind speed data collected from the National Renewable Energy Laboratory are implemented. Numerical results show that the root mean square error, mean absolute error, mean absolute percentage error, and symmetric mean absolute percentage error of this proposed model reach 0.2047, 0.1435, 3.77%, and 3.74%, respectively, which outperform the benchmark predictions using popular parameter optimization methods, data processing techniques, and hybrid neural network forecasting models. [ABSTRACT FROM AUTHOR]

In order to comprehensively utilize the remaining bamboo residue of bamboo products, this paper presents a research on recycling the bamboo fibers from bamboo residue for improving the performance of the asphalt mixtures. First of all, the basic performance parameters of sinocalamus affinis fiber, phyllostachys pubescens fiber, green bamboo fiber were tested and analyzed, and the optimal content and length were put forward. Then, the mix ratio design of the bamboo fiber modified asphalt mixture was further designed through the response surface method, and was verified the rationality of the mix ratio. Finally, the mixture specimens were made according to the experimental design mix ratio, and the high temperature, low temperature performance and moisture susceptibility of the bamboo fiber modified mixtures asphalt were tested. The results showed that the high temperature performance, low temperature performance and moisture susceptibility of bamboo fiber modified asphalt mixtures were improved compared with the performance of SBS modified asphalt mixture. When the length of bamboo fiber is 7.25 mm and the content of 0.22%, the road performance of the asphalt mixture was optimal. Consequentially, the decomposition of bamboo residue into bamboo fiber and its application in asphalt pavement can improve the reuse of bamboo waste, with remarkable environmental benefits and great promotion value. [ABSTRACT FROM AUTHOR]

The topology of brain networks is the foundation of cognition. We hypothesized that stroke damaged topological organization resulting in cognitive impairment. The aim was to explore the damage pattern of the resting-state topology in post-stroke cognitive impairment (PSCI) patients. Thirty-seven patients with PSCI and thirty-seven gender- and age-matched healthy controls (HC) were recruited. The structural and functional data were collected from all subjects. The degree centrality (DC), betweenness centrality (BC), and global properties of brain networks were analyzed between groups. Spearman correlation analysis was performed between topological properties that changed significantly and clinical cognitive function scale scores. Compared with HC, the PSCI patients had significantly reduced DC in language-related brain regions and significantly higher DC in the right frontal lobe, hippocampus, and paracentral lobule. The decreased BC was located in the left caudate, thalamus, temporal, and frontal lobes. The increased BC was detected in the left cuneus and right precuneus. In addition, PSCI exhibited increased characteristic path length and decreased small-worldness. PSCI patients had impaired functional topology of the language-related brain regions, mainly in the left hemisphere. The enhanced processing and relaying information of some right high-order cognitive brain regions may be a compensatory mechanism. However, the whole brain's function integration was reduced, and there was an imbalance between efficiency and consumption. [ABSTRACT FROM AUTHOR]

The sustainable reuse of waste plastic as an alternative construction material has numerous environmental and economic advantages. New opportunities to recycle waste plastic in asphalt for road construction would mitigate landfill issues and significantly reduce global carbon emissions. With a clear aim to contribute to a more efficient reuse of waste plastic, this paper reutilized two types of waste plastic (polypropylene (PP) and polyethylene (PE)) as asphalt modifiers to improve the performance of asphalt pavement as well as to achieve the purpose of sustainable recycling waste plastic. Therefore, the optimal preparation parameters of plastic-modified asphalt were recommended by the orthogonal test. Then, the dispersion and modification mechanisms of plastic particles in plastic-modified asphalt were further studied by Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetric Differential Scanning Calorimetry (TG-DSC). The results show that the asphalt containing PP and PE shows better overall performance at high temperatures compared with the base asphalt. Furthermore, PE-modified asphalt and PP-modified asphalt exhibited optimal properties when prepared at 3000 rpm for 30 min at 170 °C. Moreover, the results of the expansion mechanism show that the main reaction process of plastic asphalt is a physical change. Finally, PP-modified asphalt and PE-modified asphalt generally perform well and are suitable for high-temperature areas. Consequentially, the results of this research promote the recycling of waste plastic, ultimately advocating the recycling of waste materials and environmental protection of pavement construction. [ABSTRACT FROM AUTHOR]

Background: Uterine adenomyosis is associated with chronic pelvic pain, abnormal uterine bleeding, and infertility. The pathogenesis of adenomyosis is still unclear. Circular RNAs (circRNAs) have been implicated in several benign diseases and malignant tumors. We aimed to explore the co-dysregulated circular RNA profile in the eutopic endometrium and endometrial-myometrial interface (EMI) of adenomyosis.Methods: Total RNA was extracted from the eutopic endometrium and EMI of 5 patients with adenomyosis and 3 patients without adenomyosis. Next-generation sequencing was performed to identify the circRNA expression profile of the two tissue types. Bioinformatics analysis was performed to predict circRNA-binding miRNAs and miRNA-binding mRNAs and construct ceRNA networks, and functional enrichment analysis was performed to predict the biological functions of circRNAs.Results: Among the adenomyosis patients, 760 circRNAs were significantly upregulated and 119 circRNAs were significantly downregulated in the EMI of adenomyosis, while 47 circRNAs were significantly upregulated and 17 circRNAs were significantly downregulated in the eutopic endometrium of adenomyosis. We identified hsa_circ_0002144 and hsa_circ_0005806 as co-upregulated and hsa_circ_0079536 and hsa_circ_0024766 as co-downregulated in the eutopic endometrium and EMI. Bioinformatics analysis was performed to construct a ceRNA network of codifferentially expressed circRNAs. The MAPK signaling pathway is the most important signaling pathway involved in the function of the ceRNA network.Conclusions: Co-dysregulated circRNAs were present in the eutopic endometrium and EMI of adenomyosis. MiRNA binding sites were observed for all of these circRNAs and found to regulate gene expression. Co-dysregulated circRNAs may induce the eutopic endometrial invagination process through the MAPK signaling pathway and promote the progression of adenomyosis. [ABSTRACT FROM AUTHOR]

In this paper, we consider the joint replenishment and delivery scheduling of the one‐warehouse, n$n$‐retailer system with stochastic demand. In this distribution system, items are first jointly replenished and therefore can share a major ordering cost. Then a coordinated delivery scheduling is adopted to arrange the delivery plan. The problem is formulated as a mixed integer nonlinear program. Subsequently, we introduce two algorithms to handle this complex problem: a Lipschitz optimization method and a modified RAND heuristic. Numerical experiments show that the proposed methods are quite efficient. Sensitivity analysis also shows some interesting findings in terms of management. [ABSTRACT FROM AUTHOR]

Traffic target tracking is a core task in intelligent transportation system because it is useful for scene understanding and vehicle autonomous driving. Most state-of-the-art (SOTA) multiple object tracking (MOT) methods adopt a two-step procedure: object detection followed by data association. The object detection has made great progress with the development of deep learning. However, the data association still heavily depends on hand crafted constraints, such as appearance, shape, and motion, which need to be elaborately trained for a special object. In this study, a spatial-temporal encoder-decoder affinity network is proposed for multiple traffic targets tracking, aiming to utilize the power of deep learning to learn a robust spatial-temporal affinity feature of the detections and tracklets for data association. The proposed spatial-temporal affinity network contains a two-stage transformer encoder module to encode the features of the detections and the tracked targets at the image level and the tracklet level, aiming to capture the spatial correlation and temporal history information. Then, a spatial transformer decoder module is designed to compute the association affinity, where the results from the two-stage transformer encoder module are fed back to fully capture and encode the spatial and temporal information from the detections and the tracklets of the tracked targets. Thus, efficient affinity computation can be applied to perform data association in online tracking. To validate the effectiveness of the proposed method, three popular multiple traffic target tracking datasets, KITTI, UA-DETRAC, and VisDrone, are used for evaluation. On the KITTI dataset, the proposed method is compared with 15 SOTA methods and achieves 86.9% multiple object tracking accuracy (MOTA) and 85.71% multiple object tracking precision (MOTP). On the UA-DETRAC dataset, 12 SOTA methods are used to compare with the proposed method, and the proposed method achieves 20.82% MOTA and 35.65% MOTP, respectively. On the VisDrone dataset, the proposed method is compared with 10 SOTA trackers and achieves 40.5% MOTA and 74.1% MOTP, respectively. All those experimental results show that the proposed method is competitive to the state-of-the-art methods by obtaining superior tracking performance. [ABSTRACT FROM AUTHOR]

Background: Inadequate scaffolding performance hinders the clinical application of the biodegradable zinc alloy stents.Objective: In this study we propose a novel stent with the tenon-and-mortise structure to improve its scaffolding performance.Methods: 3D models of stents were established in Pro/E. Based on the biodegradable zinc alloy material and two numerical simulation experiments were performed in ABAQUS. Firstly, the novel stent could be compressed to a small-closed ring by a crimp shell and can form a tenon-and-mortise structure after expanded by a balloon. Finally, 0.35 MPa was applied to the crimp shell to test the scaffolding performance of the novel stent and meanwhile compare it with an ordinary stent.Results: Results showed that the novel stent decreased the recoiling ratio by 70.7% compared with the ordinary stent, indicating the novel structure improved the scaffolding performance of the biodegradable zinc alloy stent.Conclusion: This study proposes a novel design that is expected to improve the scaffolding performance of biodegradable stents. [ABSTRACT FROM AUTHOR]

Background: Stroke is an important cause of cognitive impairment. Rich club organization, a highly interconnected network brain core region, is closely related to cognition. We hypothesized that the disturbance of rich club organization exists in patients with post-stroke cognitive impairment (PSCI). Methods: We collected data on resting-state functional magnetic resonance imaging (rs-fMRI) with 21 healthy controls (HC), 16 hemorrhagic stroke (hPSCI), and 21 infarct stroke (iPSCI). 3D shape features and first-order statistics of stroke lesions were extracted using 3D slicer software. Additionally, we assessed cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). Results: Normalized rich club coefficients were higher in hPSCI and iPSCI than HC at low-degree k -levels (k = 1–8 in iPSCI, k = 2–8 in hPSCI). Feeder and local connections were significantly decreased in PSCI patients versus HC, mainly distributed in salience network (SN), default-mode network (DMN), cerebellum network (CN), and orbitofrontal cortex (ORB), especially involving the right and left caudate with changed nodal efficiency. The feeder and local connections of significantly between-group difference were positively related to MMSE and MoCA scores, primarily distributed in the sensorimotor network (SMN) and visual network (VN) in hPSCI, SN, and DMN in iPSCI. Additionally, decreased local connections and low-degree ϕnorm(k) were correlated to 3D shape features and first-order statistics of stroke lesions. Conclusion: This study reveals the disrupted low-degree level rich club organization and relatively preserved functional core network in PSCI patients. Decreased feeder and local connections in cognition-related networks (DMN, SN, CN, and ORB), particularly involving the caudate nucleus, may offer insight into pathological mechanism of PSCI patients. The shape and signal features of stroke lesions may provide an essential clue for the damage of functional connectivity and the whole brain networks. [ABSTRACT FROM AUTHOR]

Existing topic modeling and text segmentation methodologies generally require large datasets for training, limiting their capabilities when only small collections of text are available. In this work, we reexamine the inter-related problems of "topic identification" and "text segmentation" for sparse document learning, when there is a single new text of interest. In developing a methodology to handle single documents, we face two major challenges. First is sparse information: with access to only one document, we cannot train traditional topic models or deep learning algorithms. Second is significant noise: a considerable portion of words in any single document will produce only noise and not help discern topics or segments. To tackle these issues, we design an unsupervised, computationally efficient methodology called Biclustering Approach to Topic modeling and Segmentation (BATS). BATS leverages three key ideas to simultaneously identify topics and segment text: (i) a new mechanism that uses word order information to reduce sample complexity, (ii) a statistically sound graph-based biclustering technique that identifies latent structures of words and sentences, and (iii) a collection of effective heuristics that remove noise words and award important words to further improve performance. Experiments on six datasets show that our approach outperforms several state-of-the-art baselines when considering topic coherence, topic diversity, segmentation, and runtime comparison metrics. [ABSTRACT FROM AUTHOR]

Deterministic optimization has been successfully applied to a series of design problems of square thin-walled energy absorption tubes and to a certain extent has fulfilled great expectations for the application of such structures in subway vehicles. However, most studies have not considered the uncertainty of parameters or the correlation of uncertainty parameters, leaving little or no tolerance and resulting in over-conservative structural design. This research proposes a multi-objective uncertain method with an ellipsoid-based model to address the effects of parametric uncertainties of a centrally symmetrical square tube with diaphragms (CSSTD) on design optimization, in which the ellipsoid model is adopted to describe the related uncertainty parameters. The nonlinear interval number programming method coupled with a reliability-based possibility degree of interval (RPDI) model is introduced to handle the transformation of uncertain optimization problems. Simultaneously, local-densifying technology is adopted to enhance the local accuracy of the approximate model. Finally, the outer layer of the micro multi-objective genetic algorithm (μMOGA) combined with the inner layer of the intergeneration projection genetic algorithm (IP-GA) is applied to solve the Pareto optimal solution set of the transformed deterministic optimization. The optimization results indicate that the proposed multi-objective uncertain optimization with an ellipsoid-based model not only guarantees the crashworthiness of the CSSTD, but also improves the design robustness, which means that the proposed method can provide insightful information for crashworthiness design of subways. [ABSTRACT FROM AUTHOR]

Stroke causes alterations in local spontaneous neuronal activity and related networks functional connectivity. We hypothesized that these changes occur in patients with post-stroke cognitive impairment (PSCI). Fractional amplitude of low-frequency fluctuations (fALFF) was calculated in 36 patients with cognitive impairment, including 16 patients with hemorrhagic stroke (hPSCI group), 20 patients with ischemic stroke (iPSCI group). Twenty healthy volunteers closely matched to the patient groups with respect to age and gender were selected as the healthy control group (HC group). Regions with significant alteration were regarded as regions of interest (ROIs) using the one-way analysis of variance, and then the seed-based functional connectivity (FC) with other regions in the brain was analyzed. Pearson correlation analyses were performed to investigate the correlation between functional indexes and cognitive performance in patients with PSCI. Our results showed that fALFF values of bilateral posterior cingulate cortex (PCC)/precuneus and bilateral anterior cingulate cortex in the hPSCI group were lower than those in the HC group. Compared with the HC group, fALFF values were lower in the superior frontal gyrus and basal ganglia in the iPSCI group. Correlation analysis showed that the fALFF value of left PCC was positively correlated with MMSE scores and MoCA scores in hPSCI. Besides, the reduction of seed-based FC values was reported, especially in regions of the default-mode network (DMN) and the salience network (SN). Abnormalities of spontaneous brain activity and functional connectivity are observed in PSCI patients. The decreased fALFF and FC values in DMN of patients with hemorrhagic and SN of patients with ischemic stroke may be the pathological mechanism of cognitive impairment. Besides, we showed how to use fALFF values and functional connectivity maps to specify a target map on the cortical surface for repetitive transcranial magnetic stimulation (rTMS). [ABSTRACT FROM AUTHOR]

Prominent gaps exist between science and practice in the field of nature-based solutions (NBS) worldwide, with relatively well formulated concepts but less clear application procedures. China urgently needs to address this gap because many so called NBS practices advance rapidly nowadays, including river landscapes. Advocating planning as a bridging procedure in China's top down governance system, this study introduces NBS planning for the Jialing River in Wusheng County to address three challenges: how to transform the riverfront planning from specialized to holistic, how to effectively communicate NBS in planning, and how to incorporate both scientific results and local wisdom into NBS decision-making. A planning scope was negotiated to incorporate holistic solutions. Five NBS paradigms were identified for better communication, and then spatially allocated with specific design guidelines and governance strategies. Our pilot study calls for reflection on the communication of NBS to the public, and alternative models of NBS implementations customized to different government regimes. [ABSTRACT FROM AUTHOR]

The transient characteristics of short‐circuit current (SCC) in doubly‐fed induction generator (DFIG) are quite different from the widely researched conventional synchronous machines. However, the second harmonic characteristics of SCC that impact the reliability of the transformer protection have not been accurately analysed. This paper presents the generation mechanism of second harmonic SCC in DFIG by deducing the dynamic response of rotor‐side converter, with particular attention to the influences of the voltage drop, harmonic component of stator voltage, frequency coupling, and deviation of the phase‐locked loop. When grid fault occurs, the terminal voltage sag leads to fluctuations in the active power, then the response of converter to power fluctuation and the frequency coupling leads to the second harmonic current in the abc reference frame. And the second harmonic current injected into the grid leads to fluctuations in the voltage disturbance term and deviation of the phase‐locked loop, which, in turn, affects the second harmonic current. Based on the analysis, the mitigation measures for the second harmonic current are proposed. Simulations are implemented to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

Based on the hot compression experiment of GH4169 superalloy, the constitutive equation and the microstructure evolution model of GH4169 superalloy were established, and they were introduced into the Deform® simulation software to realize the simulation of the microstructure evolution of GH4169 superalloy in closed multidirectional forging, single-sided open multidirectional forging, and bilateral open multidirectional forging. The neural network prediction model of the microstructure of GH4169 superalloy in multidirectional forging was established using MATLAB, and the neural network prediction of microstructure evolution in three kinds of multidirectional forging was determined. Experimental results show that the prediction error of the two methods for the recrystallized grain size doesn't exceed 10%, and the error under high pass is small. For the recrystallization volume fraction, the prediction errors of the two methods are less than 3.5%, and the prediction error of the neural network for higher pass deformation is lower than the finite element simulation. The established neural network model has high prediction accuracy and can be used to predict the microstructure evolution of GH4169 during hot deformation. [ABSTRACT FROM AUTHOR]

Peatlands are a large carbon reservoir. Yet the quantification of their carbon stock still has a large uncertainty due to lacking observational data and well‐tested peatland biogeochemistry models. Here, a process‐based peatland model was calibrated using long‐term peat carbon accumulation data at multiple sites in North America. The model was then applied to quantify the peat carbon accumulation rates and stocks within North America over the last 12,000 years. We estimated that 85–174 Pg carbon was accumulated in North American peatlands over the study period including 0.37–0.76 Pg carbon in subtropical peatlands. During the period from 10,000 to 8,000 years ago, the warmer and wetter conditions might have played an important role in stimulating peat carbon accumulation by enhancing plant photosynthesis. Enhanced peat decomposition due to warming slowed the carbon accumulation through the rest of the Holocene. While recent modeling studies indicate that the northern peatlands will continue to act as a carbon sink in this century, our studies suggest that future enhanced peat decomposition accompanied by peatland areal changes induced by permafrost degradation and other disturbances shall confound the sink and source analysis. Key Points: A peatland biogeochemistry model was parameterized and tested using long‐term peat carbon accumulation rate dataThe model estimated that 85–174 Pg C was accumulated in North American peatlands during the last 12,000 yearsDuring the Holocene Thermal Maximum, the warmer and wetter conditions might have resulted in the carbon accumulation peak by enhancing plant photosynthesis in the region [ABSTRACT FROM AUTHOR]

As a promising non-invasive technique, functional near-infrared spectroscopy (fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery (MI) based on fNIRS; ten healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex. A combination of ensemble empirical mode decomposition and independent component analysis method was used to solve the signal-noise frequency spectrum aliasing issues caused by the Mayer wave (0.1 Hz), then the signal means features were extracted as an input of linear discriminant analysis and support vector machine (SVM) classifier. The SVM classifier shows better classification results, and the average accuracies of four directions, up-down and left-right were 40.55%, 73.05%, and 70.7%, respectively, using oxygenated hemoglobin (8–21 s). This paper demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index. [ABSTRACT FROM AUTHOR]

Few studies have explored the role of Cenozoic tectonic evolution in shaping the patterns and processes of extant animal distributions in and around East Asia. In this study, we selected South Chinese brown frogs as a model to examine the phylogenetic and biogeographical consequences of Miocene tectonic events within South China and its margins. We used mitochondrial and nuclear molecular data to reconstruct phylogenetic interrelationships among Chinese brown frogs using Bayesian and maximum likelihood analyses. The phylogeny results show that there are four main clades of Chinese brown frogs. Excepting the three commonly known Chinese brown frog species groups, R. maoershanensis forms an independent clade nearest to the R. japonica group. Phylogeny and P-distance analyses confirmed R. maoershanensis as a valid species. Among South Chinese brown frogs, there are four subclades associated with four geographical areas: (I) R. maoershanensis; (II) R. japonica; (III) R. chaochiaoensis; and (IV) other species of the R. longicrus species group. Divergence times, estimated using mitochondrial sequences, place the vicariance events among the four subclades in the middle to late Miocene epoch. Our results suggest that (1) South Chinese brown frogs originated due to a vicariance event separating them from the R. chensinensis species group at the time of the Geological movement (~18 million years ago, Ma) in southern Tibet and the Himalayan region; (2) the separation and speciation of R. maoershanensis from the R. japonica group occurred due to the dry climate at approximately 16 Ma; (3) South Chinese brown frogs migrated from South China to Japan at the time (~10.8 Ma) that the global sea-level fell and the East China Sea Shelf Basin was swamp facies, when a land gallery may have formed across the sea to connect the two areas; and (4) R. chaochiaoensis separated from other species of the R. longicrus species group during the uplift of the Tibetan Plateau at approximately 9.5 Ma. [ABSTRACT FROM AUTHOR]

Chytridiomycosis, caused by chytrid fungus, is a dominant infectious disease in anura after metamorphosis. Previous evidence suggests that Africa is the birthplace of chytridiomycosis. At present, with the increasingly rapid development of international trade in amphibians, the rapid spread and widespread outbreak of chytridiomycosis poses a huge threat to amphibian populations in the world. In this study, according to the entry-exit inspection and quarantine standards of the peoples Republic of China, the impact of amphibian importation from South Africa on ecological security in China was analyzed based on release assessment, contact exposure assessment and consequence assessment, to investigate the risk of chytrid fungus through the importation of amphibians from South Africa to China and the possibility of the colonization and dissemination of chytrid fungus after the introduction. The result of risk assessment of chytrid fungus through the importation of amphibians from South Africa to China and the result of possibility assessment of the colonization and dissemination of chytrid fungus after the introduction were both identified as "moderate", which indicated that the importation of amphibians from South Africa to China exhibited a certain risk, and the introduction of chytrid fungus in China would cause certain risk of colonization and dissemination. [ABSTRACT FROM AUTHOR]

[Objective] Chytridiomycosis has become one of the important infectious diseases of amphibians around the world since 1998. So far, amphibian chytridiomycosis has led to regional extinction of nearly 200 kinds of amphibians and reduced 50% of amphibian populations in the world. In recent years, amphibian chytridiomycosis occurs frequently in Europe. For instance, amphibian chytridiomycosis cases have been found successively in Spain, Germany and Italy, especially in Germany. Currently, with the development of prosperous world trade, the spread of chytrid fungus through trade between countries has posed a huge potential threat to the ecological security of amphibians in China. [Method] According to entry-exit inspection and quarantine standards of the people's Republic of China, in this paper, release assessment, contact exposure assessment and consequence assessment technologies were integrated to obtain the risk assessment result of chytrid fungus from Europe and the possibility assessment result of the colonization and dissemination of chytrid fungus after the introduction. [Result] The risk assessment result of chytrid fungus from Europe to China was identified as "moderate", and the possibility assessment result of the colonization and dissemination of chytrid fungus after the introduction was identified as " high" . [Conclusion] The importation of amphibians from Europe to China exhibits a certain risk. The introduction of chytrid fungus in China will cause a high risk of colonization and dissemination. [ABSTRACT FROM AUTHOR]

To explore hemodynamic interaction between the human respiratory system (RS) and cardiovascular system (CVS), here we propose an integrated computational model to predict the CVS hemodynamics with consideration of the respiratory fluctuation (RF). A submodule of the intrathoracic pressure (ITP) adjustment is developed and incorporated in a 0-1D multiscale hemodynamic model of the CVS specified for infant, adolescent, and adult individuals. The model is verified to enable reasonable estimation of the blood pressure waveforms accounting for the RF-induced pressure fluctuations in comparison with clinical data. The results show that the negative ITP caused by respiration increases the blood flow rates in superior and inferior vena cavae; the deep breathing improves the venous return in adolescents but has less influence on infants. It is found that a marked reduction in ITP under pathological conditions can excessively increase the flow rates in cavae independent of the individual ages, which may cause the hemodynamic instability and hence increase the risk of heart failure. Our results indicate that the present 0-1D multiscale CVS model incorporated with the RF effect is capable of providing a useful and effective tool to explore the physiological and pathological mechanisms in association with cardiopulmonary interactions and their clinical applications. [ABSTRACT FROM AUTHOR]

This paper addresses the effect of gear steel on distortion and residual stresses due to phase transformation in carburizing and quenching. In particular, the martensitic and bainitic phase transformation expansion and transformation plasticity properties of two automotive gearbox steels (20CrMnTiH and 20MnCr5) and their physical parameters are measured by experiments of transformation plasticity properties. Numerical simulations of the actual carburizing and quenching process of the gearbox spline helical gears were carried out in combination with the thermal and mechanical properties with temperature variations calculated by the material design software JMAT-Pro. In particular, the phase transformation properties of the two materials and their influence on the distortion and residual stresses after carburizing and quenching were verified by experiments of transformation plasticity and numerical simulations. A reliable basis is provided for predicting the distortion mechanism of gear steels in carburizing and quenching. [ABSTRACT FROM AUTHOR]

In the original publication, the given names and surnames of the authors were swapped in one of the references and hence incorrectly cited as Blal et al. 2017 in the article. [ABSTRACT FROM AUTHOR]

This study investigates three processes of multidirectional forging (MDF), namely, closed MDF (CMDF), single-open MDF, and double-open MDF, by using a constitutive equation and a dynamic recrystallization model of hot deformation of the GH4169 superalloy. The microstructure evolution of the three processes is simulated and compared. Among the three processes, the double-open MDF obtains the highest recrystallization degree, followed by the CMDF and the single-open MDF under the same reduction. The recrystallization degree of CMDF reaches 99.5% at 1000 °C and 9 passes, and the average recrystallized grain size is small, which is approximately 8.1 μm. The double-open MDF can obtain a fine grain size of forgings at 9 passes and 1000 °C, and it is easy to obtain forgings with the single-open MDF with uniform performance. The temperature is 850 °C–1000 °C, the compression rate is 0.15–0.2, and the pass is 5–9, which are the suitable parameter selection ranges for the CMDF. The temperature is 950 °C–1000 °C, the compression rate is 0.1–0.2, and the pass is 7–9, which are the suitable parameter selection ranges for single-open MDF. The temperature is 850 °C–1000 °C, the compression rate is 0.1–0.2, and the pass is 6–9, which are the suitable parameter selection ranges for the double-open MDF. [ABSTRACT FROM AUTHOR]

Simple Summary: Animals living in variable environments require flexible nutritional strategies for dealing with nutritional uncertainty. We investigated the diet and macro-nutritional strategies of male and female moose in six sites in northeast China, representing variable habitat quality and using spatially explicit capture-recapture to determine the local population density of moose during the snowy seasons. The moose populations experienced different forage availability and quality. Female and male moose equally tended to maintain a specifically balanced diet with a high ratio of protein and total nonstructural carbohydrates (N:C) across all populations, despite their differences in forage availability. A higher ratio of N:C in the vegetation was a positive indicator for population density. The distribution area of moose in China has been shrinking back toward the north and northeast because of climate change and human disturbance, and the population number has been declining. Between 2011 and 2015, we studied moose at six sites in the northeast of China during the snowy seasons. We collected fecal samples and plant samples that were used to estimate population densities for moose, as well as their macro-nutrient selection. Out of a total of 257 fecal samples collected at six sites, we identified a total of 120 individual moose (57 females and 63 males). The population density (moose/km2 ± SE) was highest at Hanma with 0.305 ± 0.064 moose/km2 and lowest at Meitian with only 0.028 ± 0.013 moose/km2. Forage availability was different among sites, with the lowest availability at Mohe (58.17 number/20 m2) and highest was Zhanhe (250.44 number/20 m2). Moose at Zhanhe, Hanma, and Nanwenghe had a balanced diet with higher N:C (1:7), while at Meitian, Shuanghe and Mohe the N:C was 1:8. Our results indicate that the southern areas had low forage quality and quantity and this may be the reason for the distribution of the population of moose shrinking northward. [ABSTRACT FROM AUTHOR]

This paper presented a double-open multidirectional forging with relatively few deformation passes and a uniform deformation. The constitutive equation and dynamic recrystallization model of the GH4169 superalloy were identified based on a thermal compression test and imported into Deform simulation software. The microstructure evolution law of GH4169 superalloy undergoing double-open multidirectional forging was simulated. The evolution of the recrystallization volume fraction and recrystallized grain size of the GH4169 superalloy during double-open multidirectional forging was obtained. Both higher temperatures and more passes were found to produce more complete recrystallization and smaller recrystallization grain size. At the maximum temperature studied, 1000 °C, with nine passes, the recrystallization volume fraction exceeded 95%, and the recrystallized grain size reached 3–5.5 µm. [ABSTRACT FROM AUTHOR]